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reuters-gpt2-text-gen – AI Model by fawad-aziz | AlphaNeural AI
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reuters-gpt2-text-gen
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transformers
tensorboard
safetensors
gpt2
text-generation
generated_from_trainer
fawad-aziz/reuters-gpt2-text-gen
finetune
mit
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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reuters-gpt2-text-gen
This model is a fine-tuned version of
fawad-aziz/reuters-gpt2-text-gen
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 4.5102
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0005
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
4.2961
0.9972
269
4.5102
Framework versions
Transformers 4.48.2
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0
